def load_house_sales() -> ExampleTable:
"""
Load the "House Sales" dataset.
Returns
-------
ExampleTable
The "House Sales" dataset.
"""
return ExampleTable(
Table.from_csv_file(str(_path)),
column_descriptions={
"id": "A unique identifier",
"year": "Year of sale",
"month": "Month of sale",
"day": "Day of sale",
"zipcode": "Zipcode",
"latitude": "Latitude",
"longitude": "Longitude",
"sqft_lot": "Lot area in square feet",
"sqft_living": "Interior living space in square feet",
"sqft_above": "Interior living space above ground in square feet",
"sqft_basement": "Interior living space below ground in square feet",
"floors": "Number of floors",
"bedrooms": "Number of bedrooms",
"bathrooms": "Number of bathrooms.\n\n"
"Fractional values indicate that components (toilet/sink/shower/bathtub) are missing.",
"waterfront": "Whether the building overlooks a waterfront (0 = no, 1 = yes)",
"view": "Rating of the view (1 to 5, higher is better)",
"condition": "Rating of the condition of the house (1 to 5, higher is better)",
"grade": "Rating of building construction and design (1 to 13, higher is better)",
"year_built": "Year the house was built",
"year_renovated": "Year the house was last renovated.\n\n"
"A value of 0 indicates that it was never renovated.",
"sqft_lot_15nn": "Lot area of the 15 nearest neighbors in square feet",
"sqft_living_15nn": "Interior living space of the 15 nearest neighbors in square feet",
"price": "Price the house sold for in USD",
},
)